Tag Archives: RMA

We have another interesting article about environmental change in the Sahel online. For this article, we used a Random Forest classifier and remote sensing products, to model a soil map in the Senegalese Sahel. If people are interested, I can put the R code online.

Abstract: Climatic stress and anthropogenic disturbances have caused significant environmental changes in the Sahel. In this context, the importance of soil is often underrepresented. Thus, we analyze and discuss the interdependency of soil and vegetation by classifying soil types and its woody cover for a region in the Senegalese Ferlo. Clustering of 28 soil parameters led to four soil types which correspond with local Wolof denotations: Dek, Bowel, Dior and Bardial. The soil types were confirmed by a Non-metric Multidimensional-Scaling (NMDS) ordination and extrapolated via a Random Forest classifier using six significant variables derived from Landsat imagery and a digital elevation model (out-of-bag error rate: 7.3%). In addition, canopy cover was modeled using Landsat and a Reduced-Major-Axis (RMA) regression (R2 = 0.81). A woody vegetation survey showed that every soil type has its own species composition. However, 29% of Bowel regions are deforested (i.e., degraded) and interviews revealed extensive environmental changes and a strong decline and local extinction of woody species. The differences between the soil types are significant, showing that vegetation changes (i.e., degradation and greening), resilience to climatic stress and human activities largely depend on soil properties. We highlight that spatial heterogeneity is an important aspect when dealing with environmental changes in the Sahel, and local knowledge can be well used to classify spatial units by means of public Earth observation data.